Enhance distribution grid observability

This paper investigates the use of aggregated smart meter data and forecasts to enhance grid observability in medium voltage grids. Traditional approaches achieve full observability through widespread measurements, which is very cost-intensive and is further hindered by the rapid pace of renewable energy deployment. At KNG-Kärnten Netz GmbH a novel forecast and nowcast model for the medium-voltage grid is being developed, generating online quasi-measurements of load and generation for each secondary substation. Quasi-measurements are derived from aggregated offline smart meter data, providing valuable insights into grid operation even in the absence of real-time measurements. The proposed methodology uses aggregated offline smart meter data to create representative load profiles for each substation. While limitations exist, such as the impact of limited smart meter data resolution and the neglect of grid losses, these issues are being addressed through ongoing initiatives, including increased smart meter data availability and the installation of additi onal real-time measurement points. Short-term forecasts for each substation are crucial for intraday grid operation. In the future, these forecasts combined with real-time measurements will be used to calculate load flow analyses, proactively identify potential congestions and implement necessary measures to ensure a safe and reliable grid operation.